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dc.contributor.advisorAlam, Md. Golam Rabiul
dc.contributor.advisorRoy, Shaily
dc.contributor.authorAl Taawab, Abdullah
dc.contributor.authorRahman, Mahfuzzur
dc.contributor.authorIslam, Zawadul
dc.contributor.authorMustari, Nafisa
dc.date.accessioned2022-09-14T05:21:26Z
dc.date.available2022-09-14T05:21:26Z
dc.date.copyright2022
dc.date.issued2022-05
dc.identifier.otherID: 20341043
dc.identifier.otherID: 18101485
dc.identifier.otherID: 18101005
dc.identifier.otherID: 19101086
dc.identifier.urihttp://hdl.handle.net/10361/17215
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 37-39).
dc.description.abstractUprising a child is a psychological construct of parents, which is a combination of factors that evolves over time with the growth and development of the child. Parent ing style represents a set of strategies that have diverse influences on children. These approaches can create depressive symptoms in children’s minds, which can last even if they become adolescents. Moreover, these indications may affect their level of self confidence. In this research, supervised learning models are used to detect different parenting styles, depression indications of adolescents due to parenting and the level of their self-esteem. Due to the absence of publicly available data, we created our own data set of about 500 survey responses. Additionally, eleven psychological and nine linguistic attributes of Linguistic Inquiry and Word Count (LIWC) have been used to identify depression indications. Among all the supervised models, the Lo gistic Regression (LR), Gradient Boost Classifier (GBC) and Bi-Directional LSTM (Bi-LSTM) provide better results than other models. This research is capable of helping the parents to know their children’s psychology in a better way and make them have a more profound discussion on practical life.en_US
dc.description.statementofresponsibilityAbdullah Al Taawab
dc.description.statementofresponsibilityMahfuzzur Rahman
dc.description.statementofresponsibilityZawadul Islam
dc.description.statementofresponsibilityNafisa Mustari
dc.format.extent39 Pages
dc.language.isoen_USen_US
dc.publisherBrac Universityen_US
dc.rightsBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectMachine Learningen_US
dc.subjectDeep Learningen_US
dc.subjectLIWCen_US
dc.subjectNLPen_US
dc.subjectDepressionen_US
dc.subjectParenting styleen_US
dc.subjectSelf Esteemen_US
dc.subject.lcshParenting.
dc.subject.lcshMachine learning.
dc.titleDetecting self-esteem level and depressive indication due to different parenting style using supervised learning techniquesen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB. Computer Science


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